Male-Type and Prototypal Depression Trajectories for Men Experiencing Mental Health Problems
Bibliographic record
Abstract
Growing interest in gender-sensitive assessment of depression in men has seen the development of male-specific screening tools. These measures are yet to be subject to longitudinal latent modelling, which limits evidence about the ability of these tools to detect change, especially relative to established screening scales. In this study, three waves of data were collected from 234 men (38.35 years, SD = 14.09) including 3- and 6-month follow-up. Analyses focused on baseline differences and symptom trajectories for the Patient Health Questionnaire (PHQ; prototypic symptoms) and the Male Depression Risk Scale (MDRS; male-type symptoms). At baseline, men not accessing treatment reported higher MDRS scores relative to treatment-engaged men. There was no group difference for the PHQ. Internal consistency (α, ω) coefficients indicated comparable reliability for both measures across the three waves. Multidomain latent growth modelling, including current treatment engagement as a covariate, reported good model fit (CFI = 0.964, TLI = 0.986, RMSEA = 0.081, SRMR = 0.033) with differential findings for the PHQ and MDRS. Consistent with the baseline between-group analysis, current treatment effects were observed for the MDRS, but not the PHQ. Trajectory modelling for the MDRS indicated that greater severity resulted in slower improvement by 6 months. In contrast, there was no difference in the PHQ rate of change between baseline and 6 months. Findings support the psychometric utility of the MDRS as a male-specific symptom domain measure sensitive to both longitudinal change and potential treatment effects for symptomatic men, in ways not discernible by the PHQ. The MDRS may be a useful adjunctive screening tool for assessing men's depression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".